Digital imaging using a stereo camera enables capturing and/or creating three-dimensional (3D) images based partially in depth information that can be derived on basis of two or more images depicting the same scene. In a real-life digital stereo camera two or more image sensors arranged to model human vision are employed to capture respective digital images of a scene. Due to practical constraints, however, the fields of view (FOVs) of captured by two image sensors of the stereo camera are not exactly the same. Consequently, some of the image content of a first image captured using a first image sensor are not included in the image content of a second image captured using a second image sensor. In a typical example in this regard, the first and second image sensors (with respective lens assemblies) are arranged adjacent to each other, separated by a distance that corresponds to a distance between a person's eyes. Due to the different positions of the two image sensors with respect to the scene to be imaged, some of the image content in a leftmost portion of the first image are not included in the second image while, on the other hand, some of the image content in a rightmost portion of the second image is not included in the first image.
The depth information that is typically required to create a digital 3D image representing a scene may be derived on basis of disparity information that can be extracted on basis of two or more images depicting the scene. However, in the example of the first and second image sensors described above, there is no possibility to derive the disparity information for the portions of scene that are depicted only in one of the first and second images and, consequently, the resulting depth information for these image portions is either inaccurate or completely missing, thereby possibly resulting in a 3D image of compromised quality.